As is well-known, an equalizer filter may be implemented in either the direct form or the transpose form. See, for example, Chapter 9 of Principles of CMOS VLSI Design, by N. Weste and K. Eshraghian, available from Addison-Wesley Publishing Company, 1994, herein incorporated by reference. The transpose form is frequently employed because it provides a pipelined filter structure. An equalizer filter or equalizer filter configuration in this form typically employs one multiply-accumulate (MAC) unit and one delay register per tap of the equalizer filter. However, an equalizer filter may exploit the feature that the clock frequency of the MAC units employed in the equalizer filter may exceed the input data rate or signal sample rate for the filter. In such a structure or configuration, if the clock frequency of the MAC units is F times faster than the signal sample rate, F being a positive integer, fewer MAC units may be employed because the operation of the MAC units may be time-multiplexed. Therefore, a single MAC unit may be utilized in a manner to implement several taps of the filter, referred to in this context as a "filter block." In addition, a random access memory-based (RAM-based) filter architecture may exploit this time-multiplexing approach and also reduce the number of delay registers needed by using random access memory instead.
In an adaptive Least-Mean-Squared (LMS) equalizer employing a RAM-based filter architecture, referred to in this context as a RAM-based equalizer filter configuration, the equalizer filter coefficients are typically assumed to be available from storage. Thus, the adaptation or updating of the coefficients is typically performed "off-line" by an update block. The problem with such an approach is that it reduces the convergence rate of the equalizer output signal due, at least in part, to the delay introduced by "off-line" equalizer filter coefficient adaptation. It may also require additional memory. Therefore, a need exists for an update block or equalizer filter coefficient adaptation technique in which the convergence rate may be improved.